survey_2233 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
# save file
setwd("~/Dropbox/Perception_Inequality_wHannah/Survey Files/Harris 1972 Miami Presidential Election Survey, study no. 2233")
survey <- read.dta13("harris_s2233_spss.dta")
# pid
survey$pid <- c(1:nrow(survey))
# study
survey$study <-2233
# study year (year)
survey$year <- 1972
# geographic data (urban)
survey$urban <- car::recode(survey$S13, "'Central city' = 'Urban'; 'Town' = 'Rural';
'Suburb' = 'Suburb'; 'Rural' = 'Rural'")
# geographic data (region)
survey$region <- survey$S11
levels(survey$region) <- list(East=c("East_(1)", "East_(2)"), Midwest=c("Midwest_(5)", "Midwest_(6)"),
South=c("South_(3)", "South_(4)"),
West=c("West_(7)", "West_(8)"))
class(survey$region)
# respondent head of household (hh)
survey$hh <- car::recode(survey$F2A, "'Male head' = 'Yes'; 'Female head (no male head)' = 'Yes';
'Wife' = 'No'; 'Son' = 'No'; 'Daughter' = 'No'; 'Other (specify)' = 'No';
else = 'NA'")
survey$hh <- as.factor(survey$hh)
# increasing inequality (inequality)
survey$inequality <- car::recode(survey$P12_A, "'Don t Feel' = 'Don t feel'; 'Not Sure' = 'Not sure'")
# inequality variable (inequality.variable)
survey$inequality.variable <- 1
# union (union.self)
survey$union.self <- survey$F6_1 # already harmonized
# union (union.other) question is "no union member in family?"
survey$union.other <- car::recode(survey$F6_3, "'Yes' = 'No'; 'No' = 'Yes'; else = 'NA'")
# employment (employed)
survey$employed <- survey$F2B
# occupation
survey$occupation <- survey$F2C
# household size (hhsize)
survey$hhsize <- NA
# education (educ)
survey$educ <- car::recode(survey$F5, "c('8th grade or less', 'Some high school') = 'Less than high school';
'2-yr cllg grdt (cmmnty, tc )' = 'Some college'; '4-year college graduate' = 'College graduate'")
survey$educ <- factor(survey$educ, levels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
labels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
ordered = TRUE)
# household income (income)
survey$income <- survey$F9
# age
survey$age <- survey$P1E
# race
survey$race <- survey$F10
# politics (party)
survey$party <- survey$P1C
# politics (ideology)
survey$ideology <- NA
# gender
survey$gender <- survey$F11
# religion
survey$religion <- survey$F7
# subset
survey_2233 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
summary(survey_2233)
setwd("~/Dropbox/Perception_Inequality_wHannah/Survey Files/Harris 1972 Presidential Election and Economic Outlook Survey, study no. 2235")
## packages
require("SASxport")
require("dplyr")
require("readstata13")
## download data
survey <- read.dta13("harris_s2235_spss.dta")
View(survey)
## pid
survey$pid <- c(1:nrow(survey))
class(survey$pid)
## study number
survey$study <- 2235
class(survey$study)
## year
survey$year <- 1972
class(survey$year)
## geographpic data
survey$urban <- survey$S13
summary(survey$urban)
summary(survey$S13)
survey$urban <- recode(survey$urban, `Central city` = "Urban",
`Suburb` = "Suburban", `Town` = "Rural")
## region
survey$region <- survey$S11
summary(survey$region)
summary(survey$S11)
survey$region <- recode(survey$region, `East_(1)` = "East",
`East_(2)` = "East", `South_(3)` = "South",
`South_(4)` = "South", `Midwest_(5)` = "Midwest",
`Midwest_(6)` = "Midwest", `West_(7)` = "West",
`West_(8)` = "West")
## respondent name
summary(survey$F1)
survey$hh <- survey$F1
survey$hh <- recode(survey$hh, `Male head` = "Yes",
`Female head (no male head)` = "Yes", `Wife` = "No",
`Son` = "No", `Daughter` = "No", `Other (specify)` = "No")
summary(survey$hh)
## inequality increasing
summary(survey$P6_A)
survey$inequality <- survey$P6_A
survey$inequality <- recode(survey$inequality,
`Don t feel` = "Don't Feel",
`Not sure` = "Not Sure")
summary(survey$inequality)
class(survey$inequality)
is.ordered(survey$inequality)
## inequality variable version
survey$inequality.variable <- 1
class(survey$inequality.variable)
colnames(survey)
## union
survey$union.self <- survey$F10_1
survey$union.other <- survey$F10_2
summary(survey$union.other)
## Are you employed? what kind of employment?
summary(survey$F2A)
survey$employed <- survey$F2A
class(survey$employed)
## Occupation
summary(survey$F2B)
survey$occupation <- survey$F2B
class(survey$occupation)
## household size
survey$hhsize <- NA
## Education
summary(survey$F8)
survey$educ <- survey$F8
summary(survey$educ)
survey$educ <- recode(survey$educ, `8th grade or less` = "Less than high school",
`Some high school` = "Less than high school",
`Some high school (9th-11th grade)` = "Less than high school",
`2-year college grad (community, etc )` = "Some college",
`4-year college graduate` = "College graduate")
class(survey$educ)
summary(survey$educ)
survey$educ <- as.ordered(survey$educ)
## Income
summary(survey$F9)
survey$income <- survey$F9
summary(survey$income)
class(survey$income)
## Age
summary(survey$P1E)
survey$age <- survey$P1E
summary(survey$age)
## race
summary(survey$F11)
survey$race <- survey$F11
summary(survey$race)
## politics
survey$party <- survey$P1C
summary(survey$party)
class(survey$party)
## ideology
survey$ideology <- NA
summary(survey$ideology)
## gender
summary(survey$F12)
survey$gender <- survey$F12
table(survey$gender)
## religion
survey$religion <- survey$F3
summary(survey$religion)
### put together data set
survey_2235 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
setwd("~/Dropbox/Perception_Inequality_wHannah/Survey Files/Harris 1972 Presidential Election and Economic Outlook Survey, study no. 2235")
## packages
require("SASxport")
require("dplyr")
require("readstata13")
## download data
survey <- read.dta13("harris_s2235_spss.dta")
View(survey)
## pid
survey$pid <- c(1:nrow(survey))
class(survey$pid)
## study number
survey$study <- 2235
class(survey$study)
## year
survey$year <- 1972
class(survey$year)
## geographpic data
survey$urban <- survey$S13
summary(survey$urban)
summary(survey$S13)
survey$urban <- recode(survey$urban, `Central city` = "Urban",
`Suburb` = "Suburban", `Town` = "Rural")
## region
survey$region <- survey$S11
summary(survey$region)
summary(survey$S11)
survey$region <- recode(survey$region, `East_(1)` = "East",
`East_(2)` = "East", `South_(3)` = "South",
`South_(4)` = "South", `Midwest_(5)` = "Midwest",
`Midwest_(6)` = "Midwest", `West_(7)` = "West",
`West_(8)` = "West")
## respondent name
summary(survey$F1)
survey$hh <- survey$F1
survey$hh <- recode(survey$hh, `Male head` = "Yes",
`Female head (no male head)` = "Yes", `Wife` = "No",
`Son` = "No", `Daughter` = "No", `Other (specify)` = "No")
summary(survey$hh)
## inequality increasing
summary(survey$P6_A)
survey$inequality <- survey$P6_A
survey$inequality <- recode(survey$inequality,
`Don t feel` = "Don't Feel",
`Not sure` = "Not Sure")
summary(survey$inequality)
class(survey$inequality)
is.ordered(survey$inequality)
## inequality variable version
survey$inequality.variable <- 1
class(survey$inequality.variable)
colnames(survey)
## union
survey$union.self <- survey$F10_1
survey$union.other <- survey$F10_2
summary(survey$union.other)
## Are you employed? what kind of employment?
summary(survey$F2A)
survey$employed <- survey$F2A
class(survey$employed)
## Occupation
summary(survey$F2B)
survey$occupation <- survey$F2B
class(survey$occupation)
## household size
survey$hhsize <- NA
## Education
summary(survey$F8)
survey$educ <- survey$F8
summary(survey$educ)
survey$educ <- recode(survey$educ, `8th grade or less` = "Less than high school",
`Some high school` = "Less than high school",
`Some high school (9th-11th grade)` = "Less than high school",
`2-year college grad (community, etc )` = "Some college",
`4-year college graduate` = "College graduate")
class(survey$educ)
summary(survey$educ)
survey$educ <- as.ordered(survey$educ)
## Income
summary(survey$F9)
survey$income <- survey$F9
summary(survey$income)
class(survey$income)
## Age
summary(survey$P1E)
survey$age <- survey$P1E
summary(survey$age)
## race
summary(survey$F11)
survey$race <- survey$F11
summary(survey$race)
## politics
survey$party <- survey$P1C
summary(survey$party)
class(survey$party)
## ideology
survey$ideology <- NA
summary(survey$ideology)
## gender
summary(survey$F12)
survey$gender <- survey$F12
table(survey$gender)
## religion
survey$religion <- survey$F3
summary(survey$religion)
### put together data set
survey_2235 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
summary(survey_2235)
setwd("/Users/reneelouis/Dropbox (Tapcats)/Perception_Inequality_wHannah/Survey Files/Harris 1972 Presidential Election Survey, study no. 2234")
library(dplyr)
library(tidyr)
library(car)
library(readstata13)
survey <- read.dta13("harris_s2234_spss.dta")
# pid
survey$pid <- c(1:nrow(survey))
# study
survey$study <-2234
# study year (year)
survey$year <- 1972
# geographic data (urban)
survey$urban <- car::recode(survey$S13, "'Central city' = 'Urban'; 'Town' = 'Rural'; 'Suburb' = 'Suburban'")
# geographic data (region)
survey$region <- survey$S11
levels(survey$region) <- list(East=c("East_(1)", "East_(2)"), Midwest=c("Midwest_(5)", "Midwest_(6)"),
South=c("South_(3)", "South_(4)"),
West=c("West_(7)", "West_(8)"))
class(survey$region)
# respondent head of household (hh)
survey$hh <- car::recode(survey$F2A, "'Male head' = 'Yes'; 'Female head (no male head)' = 'Yes';
'Wife' = 'No'; 'Son' = 'No'; 'Daughter' = 'No'; 'Other (specify)' = 'No';
else = 'NA'")
survey$hh <- as.factor(survey$hh)
# increasing inequality (inequality)
survey$inequality <- car::recode(survey$P7_A, "'Don t Feel' = 'Don t feel'; 'Not Sure' = 'Not sure'")
# inequality variable (inequality.variable)
survey$inequality.variable <- 1
# union (union.self)
survey$union.self <- survey$F7_1 # already harmonized
# union (union.other) question is "no union member in family?"
survey$union.other <- car::recode(survey$F7_3, "'Yes' = 'No'; 'No' = 'Yes'; else = 'NA'")
# employment (employed)
survey$employed <- survey$F2B
# occupation
survey$occupation <- survey$F2C
# household size (hhsize)
survey$hhsize <- NA
# education (educ)
survey$educ <- car::recode(survey$F5, "c('8th grade or less', 'Some high school') = 'Less than high school';
'2-yr cllg grdt (cmmnty, tc )' = 'Some college'; '4-year college graduate' = 'College graduate'")
survey$educ <- factor(survey$educ, levels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
labels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
ordered = TRUE)
# household income (income)
survey$income <- survey$F6
# age
survey$age <- survey$P1E
# race
survey$race <- survey$F8
# politics (party)
survey$party <- survey$P1C
# politics (ideology)
survey$ideology <- NA
# gender
survey$gender <- survey$F9
# religion
survey$religion <- survey$F3A
# subset
survey_2234 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
setwd("~/Dropbox/Perception_Inequality_wHannah/Survey Files/Harris 1972 Presidential Election Survey, study no. 2234")
survey <- read.dta13("harris_s2234_spss.dta")
# pid
survey$pid <- c(1:nrow(survey))
# study
survey$study <-2234
# study year (year)
survey$year <- 1972
# geographic data (urban)
survey$urban <- car::recode(survey$S13, "'Central city' = 'Urban'; 'Town' = 'Rural'; 'Suburb' = 'Suburban'")
# geographic data (region)
survey$region <- survey$S11
levels(survey$region) <- list(East=c("East_(1)", "East_(2)"), Midwest=c("Midwest_(5)", "Midwest_(6)"),
South=c("South_(3)", "South_(4)"),
West=c("West_(7)", "West_(8)"))
class(survey$region)
# respondent head of household (hh)
survey$hh <- car::recode(survey$F2A, "'Male head' = 'Yes'; 'Female head (no male head)' = 'Yes';
'Wife' = 'No'; 'Son' = 'No'; 'Daughter' = 'No'; 'Other (specify)' = 'No';
else = 'NA'")
survey$hh <- as.factor(survey$hh)
# increasing inequality (inequality)
survey$inequality <- car::recode(survey$P7_A, "'Don t Feel' = 'Don t feel'; 'Not Sure' = 'Not sure'")
# inequality variable (inequality.variable)
survey$inequality.variable <- 1
# union (union.self)
survey$union.self <- survey$F7_1 # already harmonized
# union (union.other) question is "no union member in family?"
survey$union.other <- car::recode(survey$F7_3, "'Yes' = 'No'; 'No' = 'Yes'; else = 'NA'")
# employment (employed)
survey$employed <- survey$F2B
# occupation
survey$occupation <- survey$F2C
# household size (hhsize)
survey$hhsize <- NA
# education (educ)
survey$educ <- car::recode(survey$F5, "c('8th grade or less', 'Some high school') = 'Less than high school';
'2-yr cllg grdt (cmmnty, tc )' = 'Some college'; '4-year college graduate' = 'College graduate'")
survey$educ <- factor(survey$educ, levels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
labels = c("Less than high school", "High school graduate", "Some college", "College graduate", "Post graduate"),
ordered = TRUE)
# household income (income)
survey$income <- survey$F6
# age
survey$age <- survey$P1E
# race
survey$race <- survey$F8
# politics (party)
survey$party <- survey$P1C
# politics (ideology)
survey$ideology <- NA
# gender
survey$gender <- survey$F9
# religion
survey$religion <- survey$F3A
# subset
survey_2234 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
summary(survey_2234)
setwd("~/Dropbox/Perception_Inequality_wHannah/Survey Files/Harris 1972 Presidential Election Survey, study no. 2236")
## packages
require("SASxport")
require("dplyr")
require("readstata13")
## download data
survey <- read.dta13("harris_s2236_spss.dta")
View(survey)
## pid
survey$pid <- c(1:nrow(survey))
class(survey$pid)
## study number
survey$study <- 2236
class(survey$study)
## year
survey$year <- 1972
class(survey$year)
## geographpic data
survey$urban <- NA
## region
survey$region <- NA
## respondent name
summary(survey$F1)
survey$hh <- survey$F1
survey$hh <- recode(survey$hh, `Male head` = "Yes",
`Female head (no male head)` = "Yes", `Wife` = "No",
`Son` = "No", `Daughter` = "No", `Other (specify)` = "No")
summary(survey$hh)
## inequality increasing
summary(survey$P7_A)
survey$inequality <- survey$P7_A
survey$inequality <- recode(survey$inequality,
`Dont feel` = "Don't Feel",
`Not sure` = "Not Sure")
summary(survey$inequality)
levels(survey$inequality)[2] <- "Don't Feel"
class(survey$inequality)
is.ordered(survey$inequality)
## inequality variable version
survey$inequality.variable <- 1
class(survey$inequality.variable)
## union
survey$union.self <- survey$F7_1
survey$union.other <- survey$F7_2
summary(survey$union.self)
## Are you employed? what kind of employment?
summary(survey$F2A)
survey$employed <- survey$F2A
class(survey$employed)
## Occupation
summary(survey$F2B)
survey$occupation <- survey$F2B
class(survey$occupation)
## household size
survey$hhsize <- NA
## Education
summary(survey$F5)
survey$educ <- survey$F5
summary(survey$educ)
survey$educ <- recode(survey$educ, `8th grade or less` = "Less than high school",
`Some high school` = "Less than high school",
`Some high school (9th-11th grade)` = "Less than high school",
`2-year college grad (community, etc )` = "Some college",
`4-year college graduate` = "College graduate")
class(survey$educ)
summary(survey$educ)
survey$educ <- as.ordered(survey$educ)
## Income
summary(survey$F6)
survey$income <- survey$F6
summary(survey$income)
class(survey$income)
## Age
summary(survey$P1E)
survey$age <- survey$P1E
summary(survey$age)
## race
summary(survey$F8)
survey$race <- survey$F8
summary(survey$race)
## politics
survey$party <- survey$P1C
summary(survey$party)
class(survey$party)
## ideology
survey$ideology <- NA
summary(survey$ideology)
## gender
summary(survey$F9)
survey$gender <- survey$F9
table(survey$gender)
## religion
survey$religion <- survey$F3
summary(survey$religion)
### put together data set
survey_2236 <- survey[,c("pid", "study", "year", "urban", "region", "hh",
"inequality", "inequality.variable", "union.self", "union.other",
"employed", "occupation", "hhsize", "educ", "income",
"age", "race", "party", "ideology", "gender", "religion")]
